A meta model for team recommendations

Michele Brocco; Georg Groh; Florian Forster

doi:10.1007/978-3-642-16567-2_3

A meta model for team recommendations

Michele Brocco, Georg Groh, Florian Forster

Informatics 25 - Chair of Data Science and Engineering

Technical University of Munich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Teams are an important organizational unit and need to be composed appropriately. Whenever a high number of possible team members exists, the complexity of the composition task can not be effectively handled by humans. To support the composition in this scenario, team recommenders can be used. In this paper we discuss and formalize a flexible approach using a generic meta model for implementing various team composition strategies derived from a literature review. In order to demonstrate its use and its compatibility with a generic team recommendation approach, we then translate some of the theoretical team composition approaches found in the literature.

Original language	English
Title of host publication	Social Informatics - Second International Conference, SocInfo 2010, Proceedings
Pages	35-50
Number of pages	16
DOIs	https://doi.org/10.1007/978-3-642-16567-2_3
State	Published - 2010
Event	2nd International Conference on Social Informatics, SocInfo 2010 - Laxenburg, Austria Duration: 27 Oct 2010 → 29 Oct 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6430 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Social Informatics, SocInfo 2010
Country/Territory	Austria
City	Laxenburg
Period	27/10/10 → 29/10/10

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10.1007/978-3-642-16567-2_3

Cite this

Brocco, M., Groh, G., & Forster, F. (2010). A meta model for team recommendations. In Social Informatics - Second International Conference, SocInfo 2010, Proceedings (pp. 35-50). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6430 LNCS). https://doi.org/10.1007/978-3-642-16567-2_3

@inproceedings{79be05afaadd4ce187c99cdc88ee2461,

title = "A meta model for team recommendations",

abstract = "Teams are an important organizational unit and need to be composed appropriately. Whenever a high number of possible team members exists, the complexity of the composition task can not be effectively handled by humans. To support the composition in this scenario, team recommenders can be used. In this paper we discuss and formalize a flexible approach using a generic meta model for implementing various team composition strategies derived from a literature review. In order to demonstrate its use and its compatibility with a generic team recommendation approach, we then translate some of the theoretical team composition approaches found in the literature.",

author = "Michele Brocco and Georg Groh and Florian Forster",

note = "Funding Information: Acknowledgment. This work was performed within the scope of the KoPIWA research project supported by the Federal German Ministry for Education and Research (BMBF) under contract no. 01FM07072.; 2nd International Conference on Social Informatics, SocInfo 2010 ; Conference date: 27-10-2010 Through 29-10-2010",

year = "2010",

doi = "10.1007/978-3-642-16567-2_3",

language = "English",

isbn = "3642165664",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Brocco, M, Groh, G & Forster, F 2010, A meta model for team recommendations. in Social Informatics - Second International Conference, SocInfo 2010, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6430 LNCS, pp. 35-50, 2nd International Conference on Social Informatics, SocInfo 2010, Laxenburg, Austria, 27/10/10. https://doi.org/10.1007/978-3-642-16567-2_3

A meta model for team recommendations. / Brocco, Michele; Groh, Georg; Forster, Florian.
Social Informatics - Second International Conference, SocInfo 2010, Proceedings. 2010. p. 35-50 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6430 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Groh, Georg

AU - Forster, Florian

N1 - Funding Information: Acknowledgment. This work was performed within the scope of the KoPIWA research project supported by the Federal German Ministry for Education and Research (BMBF) under contract no. 01FM07072.

PY - 2010

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N2 - Teams are an important organizational unit and need to be composed appropriately. Whenever a high number of possible team members exists, the complexity of the composition task can not be effectively handled by humans. To support the composition in this scenario, team recommenders can be used. In this paper we discuss and formalize a flexible approach using a generic meta model for implementing various team composition strategies derived from a literature review. In order to demonstrate its use and its compatibility with a generic team recommendation approach, we then translate some of the theoretical team composition approaches found in the literature.

AB - Teams are an important organizational unit and need to be composed appropriately. Whenever a high number of possible team members exists, the complexity of the composition task can not be effectively handled by humans. To support the composition in this scenario, team recommenders can be used. In this paper we discuss and formalize a flexible approach using a generic meta model for implementing various team composition strategies derived from a literature review. In order to demonstrate its use and its compatibility with a generic team recommendation approach, we then translate some of the theoretical team composition approaches found in the literature.

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DO - 10.1007/978-3-642-16567-2_3

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SN - 9783642165665

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 35

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BT - Social Informatics - Second International Conference, SocInfo 2010, Proceedings

T2 - 2nd International Conference on Social Informatics, SocInfo 2010

Y2 - 27 October 2010 through 29 October 2010

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A meta model for team recommendations

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